Research Interests

PhD Students

My research interests include

Sequential decision making and decision theory

Simulation-based dynamic optimisation / reinforcement learning Learning decision-making strategies using data or sampling from a real or a simulated environment. For example, an algorithm can learn how to play a game using a set of past games, or it can play against a human or a simulator in order to learn how to improve its behaviour.

Fully and partially observable Markov decision processes (MDPs and POMDPs) Here, an algorithm knows the parameters (dynamics) of the game, and it can perform a direct optimisation of its own strategy.

Machine learning and optimisation

Probabilistic graphical models

Compact and sparse representations for planning and reasoning

Applications of machine learning and artificial intelligence

Assistive technologies (e.g. intelligent assistants for people with cognitive disabilities)